FUCrIMODo: structure recovery from atomistic descriptors via multi-stage genetic algorithms

Data-driven approaches to materials discovery rely on numerical representations of atomic structures as input for machine learning models.

Data-driven approaches to materials discovery rely on numerical representations of atomic structures as input for machine learning models. Inverting these descriptors - recovering atomic structures from their representations - is essential for most generative material design…